An efficient non-iterative smoothed particle hydrodynamics fluid simulation method with variable smoothing length

Visual Computing for Industry, Biomedicine, and Art - Tập 6 Số 1
Min Li1, Hongshu Li1, Weiliang Meng2, Jian Zhu1, Gary Zhang3
1The School of Computer Science, Guangdong University of Technology, Guangzhou, 510006, China
2National Laboratory of Pattern Recognition, Institute of Automation of the Chinese Academy of Sciences, Beijing, 100190, China
3The School of Information Engineering, Guangdong University of Technology, Guangzhou, 510006, China

Tóm tắt

AbstractIn classical smoothed particle hydrodynamics (SPH) fluid simulation approaches, the smoothing length of Lagrangian particles is typically constant. One major disadvantage is the lack of adaptiveness, which may compromise accuracy in fluid regions such as splashes and surfaces. Attempts to address this problem used variable smoothing lengths. Yet the existing methods are computationally complex and non-efficient, because the smoothing length is typically calculated using iterative optimization. Here, we propose an efficient non-iterative SPH fluid simulation method with variable smoothing length (VSLSPH). VSLSPH correlates the smoothing length to the density change, and adaptively adjusts the smoothing length of particles with high accuracy and low computational cost, enabling large time steps. Our experimental results demonstrate the advantages of the VSLSPH approach in terms of its simulation accuracy and efficiency.

Từ khóa


Tài liệu tham khảo

Koschier D, Bender J, Solenthaler B, Teschner M (2019) Smoothed particle hydrodynamics techniques for the physics based simulation of fluids and solids. Paper presented at the 40th annual conference of the European association for computer graphics, Eurographics Association, Tutorials, 6-10 May 2019.

Ihmsen M, Orthmann J, Solenthaler B, Kolb A, Teschner M (2014) SPH fluids in computer graphics. Paper presented at the 35th annual conference of the European association for computer graphics, Eurographics Association, Strasbourg, 7-11 April 2014.

Müller M, Charypar D, Gross M (2003) Particle-based fluid simulation for interactive applications. Paper presented at the 2003 ACM SIGGRAPH/eurographics symposium on computer animation, Eurographics Association, San Diego, 26-27 July 2003.

Lyu HG, Sun PN, Huang XT, Zhong SY, Peng YX, Jiang T et al (2022) A review of SPH techniques for hydrodynamic simulations of ocean energy devices. Energies 15(2):502. https://doi.org/10.3390/en15020502

Adams B, Pauly M, Keiser R, Guibas LJ (2007) Adaptively sampled particle fluids. Paper presented at the ACM SIGGRAPH 2007, ACM, San Diego, 5-9 August 2007. https://doi.org/10.1145/1275808.1276437

Sun PN, Le Touzé D, Oger G, Zhang AM (2021) An accurate SPH Volume Adaptive Scheme for modeling strongly-compressible multiphase flows. Part 1: numerical scheme and validations with basic 1D and 2D benchmarks. J Comput Phys 426:109937. https://doi.org/10.1016/j.jcp.2020.109937

Solenthaler B, Pajarola R (2009) Predictive-corrective incompressible SPH. Paper presented at the ACM SIGGRAPH 2009, ACM, New Orleans, August 3-7 2009. https://doi.org/10.1145/1576246.1531346

Ihmsen M, Cornelis J, Solenthaler B, Horvath C, Teschner M (2014) Implicit incompressible SPH. IEEE Trans Vis Comput Graph 20(3):426-435. https://doi.org/10.1109/TVCG.2013.105

Bender J, Koschier D (2015) Divergence-free smoothed particle hydrodynamics. Paper presented at the 14th ACM SIGGRAPH/eurographics symposium on computer animation, ACM, Los Angeles, 7-9 August 2015. https://doi.org/10.1145/2786784.2786796

Bender J, Koschier D (2017) Divergence-free SPH for incompressible and viscous fluids. IEEE Trans Vis Comput Graph 23(3):1193-1206. https://doi.org/10.1109/TVCG.2016.2578335

Qiang HF, Gao W (2008) SPH method with fully variable smoothing lengths and implementation. Chin J Comput Phys 25(5):569-575.

Khayyer A, Shimizu Y, Gotoh H, Nagashima K (2021) A coupled incompressible SPH-hamiltonian SPH solver for hydroelastic FSI corresponding to composite structures. App Math Model 94:242-271. https://doi.org/10.1016/j.apm.2021.01.011

Lyu HG, Sun PN, Huang XT, Chen SH, Zhang AM (2021) On removing the numerical instability induced by negative pressures in SPH simulations of typical fluid-structure interaction problems in ocean engineering. Appl Ocean Res 117:102938. https://doi.org/10.1016/j.apor.2021.102938

Becker M, Teschner M (2007) Weakly compressible SPH for free surface flows. Paper presented at the 2007 ACM SIGGRAPH/eurographics symposium on computer animation, Eurographics Association, San Diego, 2-4 August 2007.

Wu ML, Liu SG, Xu Q (2021) Improved divergence-free smoothed particle hydrodynamics via priority of divergence-free solver and SOR. Comput Anim Virtual Worlds 32(3-4):e2006. https://doi.org/10.1002/cav.2006

Yang T, Martin RR, Lin MC, Chang J, Hu SM (2007) Pairwise force SPH model for real-time multi-interaction applications. IEEE Trans Vis Comput Graph 23(10):2235-2247. https://doi.org/10.1109/TVCG.2017.2706289

Weiler M, Koschier D, Brand M, Bender J (2018) A physically consistent implicit viscosity solver for SPH fluids. Comput Graph Forum, 37(2):145-155. https://doi.org/10.1111/cgf.13349

Band S, Gissler C, Ihmsen M, Cornelis J, Peer A, Teschner M (2018) Pressure boundaries for implicit incompressible SPH. ACM Trans Graph 37(2):14. https://doi.org/10.1145/3180486

Bender J, Kugelstadt T, Weiler M, Koschier D (2019) Volume maps: an implicit boundary representation for SPH. Paper presented at the 12th ACM SIGGRAPH conference on motion, interaction and games, ACM, Newcastle upon Tyne, 28-30 October 2019. https://doi.org/10.1145/3359566.3360077

Bender J, Kugelstadt T, Weiler M, Koschier D (2020) Implicit frictional boundary handling for SPH. IEEE Trans Vis Comput Graph 26(10):2982-2993. https://doi.org/10.1109/TVCG.2020.3004245

Gissler C, Peer A, Band S, Bender J, Teschner M (2019) Interlinked SPH pressure solvers for strong fluid-rigid coupling. ACM Trans Graph 38(1):5. https://doi.org/10.1145/3284980

Ihmsen M, Akinci N, Akinci G, Teschner M (2012) Unified spray, foam and air bubbles for particle-based fluids. Vis Comput 28(6-8):669-677. https://doi.org/10.1007/s00371-012-0697-9

Schechter H, Bridson R (2012) Ghost SPH for animating water. ACM Trans Graph 31(4):61. https://doi.org/10.1145/2185520.2185557

He F, Zhang HS, Huang C, Liu MB (2022) A stable SPH model with large CFL numbers for multi-phase flows with large density ratios. J Comput Phys 453:110944. https://doi.org/10.1016/j.jcp.2022.110944

Keiser R, Adams B, Dutré P, Guibas LJ, Pauly M (2006) Multiresolution particle-based fluids. Technical Report/ETH Zurich, Department of Computer Science, p 520.

Zhang YC, Solenthaler B, Pajarola R (2008) Adaptive sampling and rendering of fluids on the GPU. Paper presented at the fifth eurographics/IEEE VGTC conference on point-based graphics, Eurographics Association, Los Angeles, 10-11 August 2008.

Orthmann J, Kolb A (2012) Temporal blending for adaptive SPH. Comput Graph Forum 31(8):2436-2449. https://doi.org/10.1111/j.1467-8659.2012.03186.x

Winchenbach R, Hochstetter H, Kolb A (2016) Constrained neighbor lists for SPH-based fluid simulations. Paper presented at the ACM SIGGRAPH/eurographics symposium on computer animation, Eurographics Association, Zurich, 11-13 July 2016.

Zhang K, Sun YJ, Sun ZG, Wang F, Chen X, Xi G (2022) An efficient MPS refined technique with adaptive variable-size particles. Eng Anal Bound Elem 143:663-676. https://doi.org/10.1016/j.enganabound.2022.07.013

Winchenbach R, Kolb A (2021) Optimized refinement for spatially adaptive SPH. ACM Trans Graph 40(1):8. https://doi.org/10.1145/3363555

Nakanishi R, Nascimento F, Campos R, Pagliosa P, Paiva A (2020) RBF liquids: an adaptive PIC solver using RBF-FD. ACM Trans Graph 39(6):170. https://doi.org/10.1145/3414685.3417794

Xiao YW, Chan S, Wang SQ, Zhu B, Yang XB (2020) An adaptive staggered-tilted grid for incompressible flow simulation. ACM Trans Graph 39(6):171. https://doi.org/10.1145/3414685.3417837

Yang XF, Kong SC (2019) Adaptive resolution for multiphase smoothed particle hydrodynamics. Comput Phys Commun 239:112-125. https://doi.org/10.1016/j.cpc.2019.01.002

Springel V, Hernquist L (2002) Cosmological smoothed particle hydrodynamics simulations: the entropy equation. Mon Not R Astron Soc 333(3):649-664. https://doi.org/10.1046/j.1365-8711.2002.05445.x

GitHub - InteractiveComputerGraphics/SPlisHSPlasH: SPlisHSPlasH is an open-source library for the physically-based simulation of fluids. https://github.com/InteractiveComputerGraphics/SPlisHSPlasH. Accessed 24 Mar 2019

Gong XF, Yang JM, Zhang SD (2016) A parallel SPH method with background grid of adaptive mesh refinement. Chin J Comput Phys 33(2):183-189

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Visual Computing for Industry, Biomedicine, and Art

Tập 6 Số 1

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